StudentIdentification
Number81552030

NameJun Osawa

Title: Multi-Objective Optimization Model for Clean Energy Vehicles Using Input-Output
TablesAbstract
The introduction of clean energy vehicles (CEVs) is expected to reduce CO 2 emissions in thetransportation sector. However, because each CEV has different internal structurescompared to gasoline vehicles (GV), the popularization of each CEV type provides different
impacts on three dimensions: industry, consumer, and the environment.
For example, if the sales volume of electric vehicles (EVs) increases, there is a concomitant
reduction in CO2 emissions at the vehicle using phase. However, there is an important tradeoff to consider: it is expected that EVs will be priced higher than GVs, increasing the financial
burden on consumers. Further, around 20–30% of the auto parts used in GVs is not requiredin EVs. In assessing new technologies, auto manufacturers consider the impact on theexisting automotive parts industry, and might exhibit a preference for models that do notcompromise the status-quo in this respect.
In other words, because each CEV has its own advantages and disadvantages, popularizing
only specific types of vehicles will not necessarily maximize societal utility.
Therefore, it is important to analyze the optimal portfolio of CEVs in order to design aneffective policy for the introduction of CEVs.
Most previous studies have mainly focused on the environmental performance of CEVs inthe running phase, failing to consider the impact on industry. In addition, previous studies
on the tools and models that calculated and analyzed the industrial ripple effect, resulting
from the spread of CEVs, were insufficient.
Furthermore, since CEVs is a product closely related to the social system, which includes
various stakeholders, it is necessary to design the models considering stakeholder
requirements.
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Therefore, the aim of this study is to develop predictive models for long-term sales volumesof CEVs, considering the stakeholder requirements and ripple effect caused by the spread ofCEVs.
Specifically, this paper proposes a new multi-objective optimization model of portfolio,
which considers utilities across three dimensions: industry, consumer, and government(environment). In addition, by using input-output tables to evaluate the differences in theparts’ structures of GVs and CEVs, this paper proposes an industrial ripple effect model thatcomprehensively calculates and analyzes the ripple effect on the economic, and employment
aspects of the industry.
Simulation results using this industrial ripple effect model show impacts on the economy,and employment in Japan of 2020 and 2030 for the predicted sales of CEVs assumed by theMinistry of the Environment in 2010. For example, simulation results indicate that
production-induced effects in Japan in 2020 are expected to increase by about 1.3 trillion
yen when compared to 2010. Also, production-induced effects in Japan in 2030 are expected
to decrease by about 5.1 trillion yen when compared to 2010.
Also, the simulation results using the multi-objective optimization model of portfolio show
the optimal portfolios in 2030 for each dimension across all scenarios of technologicalinnovation. For example, in the standard scenario about technological innovation, plug-in
hybrid electric vehicles (PHEVs) and fuel cell vehicles account for approximately 90% ofpassenger vehicle unit sales when industrial utility is prioritized. In contrast, the introductionof GVs accounts for approximately 50% of sales when the utility of consumer is prioritized.
Also, PHEVs play an important role particularly when the utility of government (environment)
is prioritized.

Key Words
Automotive industry, Clean Energy Vehicle, Input-output analysis, Optimization, Portfolio,
Supply chain, Sustainability2